Evidence map›Paper›PMID 41325603›Full record

ArticleJMIR aging2025

End User and Primary Care Physicians' Perspectives on Digital Innovations in Dementia Risk Detection: Focus on a Digital Sleep Biomarker.

Ríona Mc Ardle, Marie Poole, Sophie Horrocks, Josh King-Robson, Jonathan M Schott, David Sharp, Matthew Harrison, Louise Robinson

Abstract read
In one paragraph

Article in JMIR aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ríona Mc ArdleTranslational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, United Kingdom.ORCID https://orcid.org/0000-0001-7959-3563
Marie PoolePopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, United Kingdom.ORCID https://orcid.org/0000-0001-8379-7462
Sophie HorrocksCare Research and Technology Centre, UK Dementia Research Institute, London, United Kingdom.ORCID https://orcid.org/0000-0002-9139-2016
Josh King-RobsonQueen Square Institute of Neurology, Dementia Research Centre, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0002-3662-9404
Jonathan M SchottQueen Square Institute of Neurology, Dementia Research Centre, University College London, London, United Kingdom.ORCID https://orcid.org/0000-0003-2059-024X
David SharpCare Research and Technology Centre, UK Dementia Research Institute, London, United Kingdom.ORCID https://orcid.org/0000-0002-1034-8567
Matthew HarrisonCare Research and Technology Centre, UK Dementia Research Institute, London, United Kingdom.ORCID https://orcid.org/0000-0002-4905-5737
Louise RobinsonPopulation Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, United Kingdom.ORCID https://orcid.org/0000-0003-0209-2503

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDementia is a global health priority. Early identification in asymptomatic or mildly symptomatic individuals (ie, dementia risk detection) is proposed as a clinical solution for early intervention and could support researchers to identify novel neuropathological targets and recruit to clinical trials. Digital biomarkers of behavioral or physiological markers, including sleep, are cited as a potential low-cost, noninvasive, and objective method for dementia risk detection. Understanding perspectives on digital biomarkers, particularly acceptability, from potential end users and clinical staff is required when considering implementation within any clinical service. With emerging evidence of sleep as a risk marker for dementia, the efficacy of the Dementia Research Institute Sleep Index (DRI-SI), based on continuous remote monitoring of sleep patterns detected by a digital sleep mat, for dementia risk detection, is currently being explored by the InSleep46 study.

objectiveThis qualitative substudy aimed to explore perspectives of potential end users and primary care physicians regarding the use of a digital sleep mat to measure the DRI-SI and its application towards dementia risk detection.

methodsThirty-one potential end users (age: 31-82 years, 11 female and 20 male) from Newcastle and London, United Kingdom, with personal or caregiving experience related to dementia, participated in qualitative focus group workshops. They shared opinions on integrating the sleep mat into their homes, the DRI-SI's potential for identifying dementia risk, and the necessary information for engagement with related clinical services. Seven primary care physicians from across England participated in semistructured interviews regarding the potential application of the DRI-SI in dementia risk detection and its integration into current clinical practice. Inductive thematic analysis was conducted to identify key themes.

resultsFour key themes emerged from end user focus groups: (1) practical use, (2) prospective acceptability, (3) clinical management, and (4) data concerns. Three main themes came from the semistructured interviews with physicians: (1) prospective acceptability, (2) health care provision, and (3) practical considerations. Common themes were identified in both groups but held differing perspectives. End users were focused on practical aspects of integrating the digital sleep mat within their daily life, the effect of the DRI-SI on clinical care, and privacy concerns regarding data use. Primary care physicians were concerned more broadly with how the DRI-SI and dementia risk detection service would integrate into current clinical practice, the impact on clinical resources and patient well-being, and the need for clinical actionability and guidance on discussing results with patients.

conclusionsEnd users would find the DRI-SI acceptable as part of their clinical care, but primary care physicians require a more robust evidence base. Future research should explore the integration of the DRI-SI into clinical care/research pathways to enhance clinical acceptability. Five key recommendations have been made for further development of digital biomarkers for dementia risk populations.

Indexed as

Attitude of Health PersonnelDementiaPhysicians, Primary CareSleepAdultAgedAged, 80 and overBiomarkersFemaleFocus GroupsHumansMaleMiddle AgedQualitative ResearchBiomarkerscommunity-based participatory researchdementiadigital healthdigital technologymass screeningqualitative research

Identifiers

PMID41325603
PMCPMC12706451

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.